Update app.py

app.py

@@ -28,13 +28,25 @@ sampler_list = [
 ]
 
 examples = [
-    """
-    1girl,
+    [
+        """
+        1girl,
 midori \(blue archive\), blue archive,
 (ningen mame:0.9), ciloranko, sho \(sho lwlw\), (tianliang duohe fangdongye:0.8), ask \(askzy\), wlop,
 indoors, plant, hair bow, cake, cat ears, food, smile, animal ear headphones, bare legs, short shorts, drawing \(object\), feet, legs, on back, bed, solo, green eyes, cat, table, window blinds, headphones, nintendo switch, toes, bow, toenails, looking at viewer, chips \(food\), potted plant, halo, calendar \(object\), tray, blonde hair, green halo, lying, barefoot, bare shoulders, blunt bangs, green shorts, picture frame, fake animal ears, closed mouth, shorts, handheld game console, green bow, animal ears, on bed, medium hair, knees up, upshorts, eating, potato chips, pillow, blush, dolphin shorts, ass, character doll, alternate costume,
 masterpiece, newest, absurdres
-    """
+        """,
+        """
+        bad anatomy,blurry,(worst quality:1.8),low quality,hands bad,face bad,(normal quality:1.3),bad hands,mutated hands and fingers,extra legs,extra arms,duplicate,cropped,text,jpeg,artifacts,signature,watermark,username,blurry,artist name,trademark,title,multiple view,Reference sheet,long body,multiple breasts,mutated,bad anatomy,disfigured,bad proportions,duplicate,bad feet,artist name,ugly,text font ui,missing limb,monochrome,
+        """,
+        0,
+        1024,
+        1536,
+        5.0,
+        26,
+        "Euler a",
+        2
+    ]
 ]
 
 torch.backends.cudnn.deterministic = True
@@ -95,7 +107,7 @@ def generate(
     height: int = 1024,
     guidance_scale: float = 5.0,
     num_inference_steps: int = 26,
-    sampler: str = "Eul""er a",
+    sampler: str = "Euler a",
     clip_skip: int = 1,
     progress=gr.Progress(track_tqdm=True),
 ):
@@ -256,7 +268,17 @@ with gr.Blocks(
 
     gr.Examples(
         examples=examples,
-        inputs=prompt,
+        inputs=[
+            prompt,
+            negative_prompt,
+            seed,
+            width,
+            height,
+            guidance_scale,
+            num_inference_steps,
+            sampler,
+            clip_skip
+        ],
         outputs=[result, used_seed],
         fn=lambda *args, **kwargs: generate(*args, **kwargs),
         cache_examples=CACHE_EXAMPLES,